The growth of short-term letting platforms has changed how residential properties are used and may influence the social and commercial character of local neighbourhoods. Areas with high concentrations of short-term accommodation may experience changes in the types of businesses, services and amenities that operate locally, as well as changes in patterns of activity and community interaction.
This project will explore how technology and data analytics can be used to investigate the relationship between concentrations of short-term letting and changes in local neighbourhoods. For example, the project could examine whether areas with increasing levels of short-term letting experience changes in their retail and commercial activity, such as changes in the types or turnover of local businesses.
The project could combine publicly available data from short-term letting platforms, business directories, mapping services, local datasets and other sources to identify spatial and temporal patterns.
Key Areas:
- Data science and spatial analysis
- Short-term letting and urban environments
- Retail and commercial activity
- Geographic Information Systems (GIS)
- Data visualisation
- Web/data mining
- Social computing and urban informatics
Potential Outcome:
A prototype data-driven system or interactive map/dashboard that visualises and analyses the relationship between concentrations of short-term letting and changes in local commercial and/or social activity, providing an evidence-based view of how neighbourhoods may evolve over time.